P.012 Treatment and long-term follow-up of primary CNS classical Hodgkin’s Lymphoma – a case report and review of the literature
Bibliographic record
Abstract
Background: Unlike non-Hodgkin’s lymphoma, central nervous system involvement with classical Hodgkin’s lymphoma is exceedingly rare, thus information regarding treatment and prognostication of the disease is lacking. Methods: This case report was prepared using hospital charts, and PubMed for the literature search. Our case was compared and contrasted against similar cases in the literature. Results: We present the case of a 47 year old female who presented with a left parietal dural-based lesion which proved to be Stage IE primary CNS classical Hodgkin’s lymphoma. After surgery and whole brain radiation therapy, the patient has remained in complete remission over nine years. Conclusions: Despite the dearth of information available regarding CNS Hodgkin’s lymphoma, our case is consistent with the findings in the literature that long-term survival is possible in patients achieving a complete response to treatment, especially in those patients who present with sole CNS involvement. To our knowledge, this represents the longest reported survival in the literature and contributes to our understanding of prognosis in patients with CNS Hodgkin’s lymphoma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".